Hybrid Role – Charlotte, NC || AI Platform Engineer with Strong AWS

Hybrid Role – Charlotte, NC

Role: AWS Data & AI Platform Engineer

Location: Hybrid in Charlotte, NC, 3 days per week in client office.

Duration: 6+ months

Job Description – AI Platform Engineer (AWS – Financial Services)

Day to Day job Duties: (what this person will do on a daily/weekly basis)

·         Design, build, and operate secure, scalable AI platforms on AWS for enterprise and regulated environments

·         Develop and manage generative AI solutions using Amazon Bedrock for model integration and deployment

·         Build and operate containerized AI services on Amazon EKS supporting Python-based inference and orchestration workloads

·         Develop serverless AI workflows using AWS Lambda, API Gateway, and event-driven architectures

·         Implement secure networking and access controls using VPC, IAM, and private endpoints

·         Integrate data services such as S3, DynamoDB, and messaging/streaming platforms to enable AI pipelines and RAG architectures

·         Establish CI/CD, monitoring, logging, and operational controls aligned to enterprise and regulatory standards

·         Collaborate with security, architecture, and risk teams to ensure compliance with financial services requirements

Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)

·         Minimum 5+ years of experience building cloud platforms on AWS

·         Minimum 2+ years of experience hands-on experience with Amazon Bedrock, EKS/Kubernetes, AWS Lambda, and core AWS networking services

·         Minimum 8+ years of experience with Python development experience supporting APIs, AI services, or automation workflows

·         Minimum 5+ years of experience designing secure, highly available, and scalable distributed systems

·         Minimum 5+ years of experience working in regulated environments such as financial services, banking, or insurance

Travel:

Minimal travel required; ability to support client stakeholders in regulated environments as needed. 

Degree:

Bachelor’s degree in Computer Science, Engineering, or equivalent work experience

Nice to Have; (But not a must)

·         Experience supporting AI/ML or generative AI platforms in production

·         Knowledge of data security, model governance, auditability, and access controls

·         Experience with Infrastructure as Code (Terraform, CloudFormation, or CDK)

·         Exposure to CI/CD pipelines and production operations in enterprise environments.